Application of Machine Learning for Sensors Network Resource Management
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: closed (15 January 2024) | Viewed by 9226
Special Issue Editors
Interests: network security; cloud computing; security; computer networking; network communication; networking; information and communication technology; information technology; IT security; PHP
Special Issue Information
Dear Colleagues,
Machine learning techniques can be applied to solve various issues in computer networks. Recently, researchers have advanced the study of Network Intrusion Detection, Network Traffic Optimization, Fault Detection, Network Resource Management, and QoS Management utilizing various ML techniques ranging from reinforcement learning to federated learning. As an example, machine learning algorithms can be used to analyze network traffic and detect anomalies or suspicious activities that may indicate an intrusion or malicious behavior. By training models on labeled datasets of normal and attack traffic, machine learning can help identify patterns and classify network traffic in real-time. Similarly, machine learning can be applied to optimize network traffic and improve network performance. By analyzing historical data, machine learning algorithms can identify patterns in network traffic, predict network congestion, and optimize routing protocols to ensure efficient data transmission. Therefore, the editors seek original submissions on the following topics: FL for network resource management; ML for network traffic and content analysis; resource management using ML for fog, edge and cloud computing; network traffic prediction for resource allocation; QoS and energy management of network resources; identifying anomalous traffic patterns in IoT; and enabling blockchain-based applications for large-scale networks.
Dr. Junaid Shuja
Dr. Atta ur Rehman Khan
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- machine learning
- blockchain
- federated learning
- network resource management
- QoS
- edge computing
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue policies can be found here.